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WhatsApp Read Poll

whatsapp_read_poll
Read-only

Reads WhatsApp poll results. With poll_id: that poll's question, options and vote counts; without it: recent polls in the chat. chat_id MUST come from whatsapp_list_chats / whatsapp_list_groups. IMPORTANT — the counts are INDICATIVE, not definitive: WhatsApp poll votes are end-to-end encrypted and a vote can be silently missing if this device was unlinked when it arrived. The response includes a completeness_caveat and, for group polls, the group's participant count as the denominator. NEVER report a poll result as final without the caveat — verify the firm tally in the WhatsApp app. ⚠️ Uses Wacli (unofficial WhatsApp client). Accounts may be restricted for ToS violations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax polls when listing (default 50)
chat_idYesChat/group JID from whatsapp_list_chats/whatsapp_list_groups
poll_idNoOptional poll message ID (from a prior whatsapp_read_poll list)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the readOnlyHint/destructiveHint annotations, the description discloses that vote counts are indicative due to end-to-end encryption, that votes can be silently missing, that the response includes a completeness_caveat, and that Wacli is unofficial with account-restriction risk. This is far more behavioral context than the annotations alone provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core function and mode split, then layers caveats by importance using IMPORTANT, NEVER, and ⚠️. Every sentence carries a decision-relevant fact, and the warnings are visually scannable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present and readOnly/destructive annotations already provided, the description covers the remaining gaps: prerequisite chat_id source, provisional-data caveats, response fields, and ToS risk. An agent has everything needed to call and interpret this tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already documents all three parameters with 100% coverage, which sets a baseline of 3. The description adds meaning by explaining the optional poll_id mode, reinforcing chat_id provenance, and clarifying that omitting poll_id lists recent polls in the chat.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The opening 'Reads WhatsApp poll results' states a specific verb and resource, and the with/without poll_id explanation defines the two calling modes. It is clearly differentiated from siblings like whatsapp_send_poll and whatsapp_read_messages.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly requires chat_id to come from whatsapp_list_chats or whatsapp_list_groups and explains the with/without poll_id behavior. It could be stronger with a direct 'use this instead of X' statement, but the usage context is clear and unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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